Purpose: :
To describe an image analysis method and software for quantitativelyanalyzing corneal images obtained using an ultra-high resolutionoptical coherence tomography (OCT) and to assess its validity.

Methods: :
A custom built spectral-domain OCT with ultra-high resolution(~3 µm) was built for imaging the anterior segment. Allimages were obtained in 20 healthy subjects. Image processingsteps applied to the ultra-high resolution OCT images that wereconstructed by 2048x1365 pixels. First, the surface betweenair and anterior cornea was semi-automatically segmented by3 to 4 points on the interface and fitted in a spline polynomialmodel. Then the OCT image was processed to correct the distortiondue to the light refraction at the air- cornea interface basedon the Fermat’s principle. From the corrected image, thealgorithm semi-automatically defined the boundaries for corneaand its sub-layers by user input of 3 to 4 points. The pointswere identified by the signal peaks at the interface. The splinepolynomial model was also applied to fit the contour based onthe selected points. The corneal thickness was measured as thedistance between the anterior and posterior corneal surfacesalong lines perpendicular to the anterior surface at the pointof measurement. Along these lines, the epithelium thicknesswas also measured as the distance between the anterior cornealsurface and basal cell layer. A profile for corneal and epitheliumthickness was generated from each meridional cross section.Sixteen corneal cross sections were loaded to compute the cornealand epithelium thickness map by interpolation.

Results: :
The analysis software successfully measured all parameters inall images and dimensional results from the obtained OCT images.The corneal and epithelial thickness maps were successfullycreated and consistent with previous literature. The segmentedboundaries agreed well with visual inspection of each cross-sectionalimage.